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Names align with official administrative geography used by the Philippine Statistics Authority and the Commission on Elections. |\n| postduterte | Period flag for the administrative change on July 1, 2016: 0 indicates observations from the months before July 1, 2016; 1 indicates observations from the months on/after that date. This creates a two-period panel for each municipality. |\n| drug_related_pcap | Per\u2011capita rate of police blotter incidents related to anti\u2011illegal\u2011drugs operations in the municipality and period, scaled per 1,000 residents. Incidents are drawn from the Philippine National Police (PNP) Bantay Krimen system and follow the PNP anti\u2011illegal drugs operations manual (e.g., buy\u2011busts, search and seizure via warrant, eradication, controlled delivery, clandestine laboratory raids, in flagrante operations). Voluntary surrenders are excluded. Counts are aggregated by municipality and normalized using official population totals. |\n| interaction | Post\u2011period outsider\u2011executive indicator: equals 1 if a municipality\u2019s 2016 elected mayor is classified as a non\u2011establishment/outsider (independent or minor\u2011party) and the observation falls after July 1, 2016; 0 otherwise. Constructed from 2016 mayoral election returns and party labels that distinguish establishment (Liberal Party) from independents/minor parties. By construction, this variable is 0 in all pre\u2011period rows. |\n\nDataset Context:\nThis dataset links administrative crime records to local political context around the national administration change on July 1, 2016 in the Philippines. The core measurement of policing activity comes from the Philippine National Police\u2019s Bantay Krimen (Crime Watch) platform, which publishes geocoded police blotter entries in near\u2013real time as reported by municipal and city police stations and organized by provincial police offices. Within these records, drug-related incidents are tagged according to the Revised PNP Manual on Anti\u2011Illegal Drugs Operations and Investigation. Only events requiring active police operations are included (such as buy\u2011busts, searches by warrant, controlled deliveries, clandestine laboratory raids, eradication, or in\u2011flagrante operations); voluntary surrenders are recorded by separate agencies and are not part of this series. Incidents are aggregated to the municipality/city level and scaled per capita, allowing comparisons across differently sized localities.\n\nThe time structure of the file is a simple two\u2011period panel: one observation per municipality before July 1, 2016 and one after. This timing captures the onset of a high\u2011salience national campaign against illegal drugs and the subsequent operational phases that characterized policing during the early years of the new administration (including surges and pauses communicated via national directives). Because mayors play a formal role in local police supervision\u2014such as recommending municipal police chiefs and exercising operational oversight\u2014information on the political profile of local executives is merged using certified 2016 mayoral election returns. Party labels at that election are used to categorize mayors as establishment (Liberal Party) versus non\u2011establishment/outsider (independents and minor parties), reflecting short\u2011term access to prevailing patronage networks at the time.\n\nIn sum, the dataset provides a municipality\u2011by\u2011period view of police\u2011recorded drug operations aligned to an administrative break in mid\u20112016, with standardized geographic identifiers, a clear temporal divider, per\u2011capita scaling, and a constructed indicator that flags outsider\u2011led municipalities in the post\u2011change period. It is designed to facilitate analyses of how policing activity varied across places and time under the institutional and political conditions prevailing during this transition.","file_sha256":"1930004a6c443521fb50e5b4970b189df8b7b4b761e32d8610d307ad93c85cac","format":"csv","frame_sha256":null,"generator":null,"kind":"file","licence":"redistributed by CausalReasoningBenchmark (MIT) under the original replication data's terms","member":null,"object":null,"params":{},"path":null,"read_kw":{},"records":null,"role":"agent","sha256":"1930004a6c443521fb50e5b4970b189df8b7b4b761e32d8610d307ad93c85cac","transforms":[],"url":"https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/data/ds_0028/data/data.csv"},"ref_panel":{"columns":null,"description":"Municipality rows with the municipality's treated status","file_sha256":"1930004a6c443521fb50e5b4970b189df8b7b4b761e32d8610d307ad93c85cac","format":"csv","frame_sha256":null,"generator":null,"kind":"file","licence":"redistributed by CausalReasoningBenchmark (MIT) under the original replication data's terms","member":null,"object":null,"params":{},"path":null,"read_kw":{},"records":null,"role":"reference","sha256":"1930004a6c443521fb50e5b4970b189df8b7b4b761e32d8610d307ad93c85cac","transforms":[{"args":{"columns":["municipality","postduterte","drug_related_pcap","interaction"]},"op":"select"},{"args":{"columns":["municipality","postduterte","drug_related_pcap","interaction"]},"op":"dropna"},{"args":{"args":{"cmp":"gt","column":"postduterte","value":0},"name":"postduterte","op":"indicator"},"op":"derive"},{"args":{"args":{"cmp":"gt","column":"interaction","value":0},"name":"interaction","op":"indicator"},"op":"derive"},{"args":{"how":"inner","on":["municipality"],"with":"ref_treat"},"op":"merge"},{"args":{"args":{"columns":["treated","postduterte"]},"name":"treated_post","op":"interaction"},"op":"derive"}],"url":"https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/data/ds_0028/data/data.csv"},"ref_treat":{"columns":null,"description":"Each municipality's max of interaction over all its rows (treated)","file_sha256":"1930004a6c443521fb50e5b4970b189df8b7b4b761e32d8610d307ad93c85cac","format":"csv","frame_sha256":null,"generator":null,"kind":"file","licence":"redistributed by CausalReasoningBenchmark (MIT) under the original replication data's terms","member":null,"object":null,"params":{},"path":null,"read_kw":{},"records":null,"role":"reference","sha256":"1930004a6c443521fb50e5b4970b189df8b7b4b761e32d8610d307ad93c85cac","transforms":[{"args":{"columns":["municipality","postduterte","drug_related_pcap","interaction"]},"op":"select"},{"args":{"columns":["municipality","postduterte","drug_related_pcap","interaction"]},"op":"dropna"},{"args":{"args":{"cmp":"gt","column":"postduterte","value":0},"name":"postduterte","op":"indicator"},"op":"derive"},{"args":{"args":{"cmp":"gt","column":"interaction","value":0},"name":"interaction","op":"indicator"},"op":"derive"},{"args":{"aggs":[{"column":"interaction","fn":"max","name":"treated"}],"by":["municipality"]},"op":"collapse"}],"url":"https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/data/ds_0028/data/data.csv"}},"difficulty":"M","id":"crb_papers.q054","level":"T2","meta":{"agent_reach":{"blocked_by":["reference_frame:ref_panel","reference_frame:ref_treat"],"dtypes":{"ds_0028":{"drug_related_pcap":"float64","interaction":"float64"}},"named":{"outcome":["drug_related_pcap"],"treatment":["interaction"]},"reachable":false,"rule":"magi_bench.reach/1"},"answer_format":{"figure_transform":"identity","round_to":null,"unit_scale":1.0},"cluster":"ds_0028","crb":{"data_path":"data/ds_0028/data/data.csv","dataset_id":"ds_0028","gold":{"ci95":[0.012422002960356504,0.7105135361002572],"ci_rule":"effect \u00b1 1.96\u00b7|standard_error| (evaluate_result.ci_bounds)","effect":0.36146776953030685,"standard_error":0.17808457478058692},"identification":{"causal_quantity":"ATT","group_variable":"municipality","outcomes":["drug_related_pcap"],"strategy":"Difference-in-Differences","time_variable":"postduterte","treatments":["interaction"]},"identification_strategy":"Difference-in-Differences"},"headline_keys":{"infer.ols":["coef.treated_post"]},"item_caveats":[{"kind":"within_suite_duplicate","note":"q053 and q054 score the same estimate (gold 0.3614677695, SE 0.178085) from two scripts that build the treated status differently; scored independently, counted twice"}],"naive":{"dataset":"ds_0028","treatment":"interaction","y":"drug_related_pcap"},"native_id":"54","reference":{"cite":1,"note":"Reference path transcribed from the item's own estimation script.","steps":[{"args":{"cluster":"municipality","controls":["treated","postduterte"],"dataset":"ref_panel","x":["treated_post"],"y":"drug_related_pcap"},"tool":"infer.ols","why":"smf.ols('drug_related_pcap ~ treated + postduterte + treated:postduterte'), cluster by municipality"}]},"reference_path":{"calls":[{"args":{"cluster":"municipality","controls":["treated","postduterte"],"dataset":"ref_panel","x":["treated_post"],"y":"drug_related_pcap"},"tool":"infer.ols"}],"needs":[],"provenance":"benchmark_script","quotes":{},"reference_datasets":["ref_panel","ref_treat"],"source_id":"crb_papers.q054.script"}},"question":"Across the full sample of 189 close-election municipalities, how did the change in drug-related incident rates (per 1,000 people) from before to after July 1, 2016 differ between municipalities governed by outsider mayors and those governed by establishment-aligned mayors?","requires":[],"runner":null,"sources":["crb_papers.q054.gold","crb_papers.q054.script"],"split":"public","suite":"crb_papers","tags":["econ-bench","external","crb","did","ref_benchmark_script"],"target":"agent","tool":null,"truth":"CausalReasoningBenchmark gold at the pinned revision: causal_queries.json effect and standard_error (the value the item's estimation.py prints), scored as evaluate_result.py scores estimate_within_solution_ci"}